experiment_id = "SRP491411"

path_to_create_exp_script = "/Users/scarsana/Desktop/git/scRNA-Seq/scripts/Create_ExpLib_tables.py" 
path_to_barcodes_script = "/Users/scarsana/Desktop/git/scRNA-Seq/scripts/create_scRNASeq_barcode_v2.py"
experiment_type = "scRNA"

path_to_output_main = "/Users/scarsana/Desktop/git/expression-annotations/Notebooks/scRNA/" 
path_to_output = "{}{}/".format(path_to_output_main, experiment_id)
library_path_from_script = "{}scRNASeqLibrary_{}.tsv".format(path_to_output, experiment_id)
experiment_path_from_script = "{}scRNASeqExperiment_{}.tsv".format(path_to_output, experiment_id)
barcode_path = "{}scRNASeq_barcode_{}.tsv".format(path_to_output, experiment_id)
barcode_to_add_path = "{}complete_scRNASeq_barcode_{}.tsv".format(path_to_output, experiment_id)
library_to_add_path = "{}complete_scRNASeqLibrary_{}.tsv".format(path_to_output, experiment_id)
experiment_to_add_path = "{}complete_RNASeqExperiment_{}.tsv".format(path_to_output, experiment_id)
script_file = "{}.ipynb".format(experiment_id)
commit_message_exp = '"adding annotated scRNA experiment {}"'.format(experiment_id)
commit_message_py = '"adding annotation files for {} to notebook folder"'.format(experiment_id)



## to add to git
path_to_git_annotations = "/Users/scarsana/Desktop/git/expression-annotations/scRNA_Seq/"
git_library_path = "{}scRNASeqLibrary_merged.tsv".format(path_to_git_annotations)
git_experiment_path = "{}scRNASeqExperiment.tsv".format(path_to_git_annotations)
git_barcode_path = "{}scRNASeq_barcode_{}.tsv".format(path_to_git_annotations, experiment_id)

## columns
library_cols = ['#libraryId', 'experimentId', 'platform', 'SRSId', 'anatId', 'anatName', 'cellTypeId', 'cellTypeName', 'stageId', 'stageName', 'url_GSM', 'infoOrgan', 'infoCellType_abInitio', 'infoCellType_inferred', 'clusterId', 'clusterName', 'infoStage', 'anatAnnotationStatus', 'cellTypeAnnotationStatus', 'stageAnnotationStatus', 'sex', 'strain', 'genotype', 'speciesId', 'RNAseqTags', 'protocol', 'protocolType', 'lib_name', 'sampleName', 'comment', 'condition', 'annotatorId', 'lastModificationDate']
barcode_cols = ['barcode', 'cluster', 'library', 'experiment', 'tissue', 'cell_type', 'anatId_a_posteriori', 'anatName_a_posteriori', 'anat_a_posteriori_annotationStatus', 'cellTypeId', 'cellTypeName', 'cellTypeAnnotationStatus', 'name_Library', 'comments']

## annotation sheet paths (maybe make these into their own folder)
annotation_files_path = "{}annotation_files/".format(path_to_output)
import os
if not os.path.exists(annotation_files_path):
    os.makedirs(annotation_files_path)

info_anat_path = "{}info_anat.tsv".format(annotation_files_path)
info_anat_complete_path = "{}info_anat_complete.tsv".format(annotation_files_path)
info_stage_path = "{}info_dev_stage.tsv".format(annotation_files_path)
info_stage_complete_path = "{}info_dev_stage_complete.tsv".format(annotation_files_path)
info_celltype_path = "{}info_celltype.tsv".format(annotation_files_path)
info_celltype_complete_path = "{}info_celltype_complete.tsv".format(annotation_files_path)

## barcode file & matching library names - 10X only
path_to_barcode_file = "{}barcode_{}.tsv".format(path_to_output, experiment_id)
lib_names_path = "{}matching_lib_names_{}.tsv".format(path_to_output, experiment_id)

# cell type annotations
display_df(cell_df_complete)

# organ annotations
display_df(organ_df_complete)

# stage annotations
display_df(stage_df_complete)

import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import pandas as pd
import numpy as np
from IPython.display import display, HTML
import csv

# displays df with the scrollbar next to the DataFrame
def display_df(df):
    pd.set_option("display.max_rows", None)
    pd.set_option("display.max_columns", None)
    display(HTML("<div style='height: 300px; overflow: auto; width: fit-content'>" +
        df.style.to_html(index=False) + "</div>"))

# function that compares two columns in a dataframe and tells you which ones are not equal (case insensitive)
def compare_columns(df, col1, col2, return_col):
    compare_return = df[col1].str.lower() != df[col2].str.lower()  
    df.loc[compare_return, return_col] 
    if not any(compare_return):
        print("The two columns are equal (case insensitive)")
    else:
        print("The following rows are not equal: ")
        print(df.loc[compare_return, return_col])

# fixes formatting of file to match libreoffice settings/historic file format
def update_format(path):
    with open(path, 'r') as file:
        filedata = file.read()
    # Replace the target string
    filedata = filedata.replace("\t\"\"", "\t")
    # Write the file out again
    with open(path, 'w') as file:
        file.write(filedata)

# checks for duplicate values in a specific column and prints those values + the corresponding library id
def dup_check(df, column):
    duplicateCheck = df.duplicated(subset=[column], keep=False)
    if duplicateCheck.unique() == False:
        print("no duplicate values in " + column)
    elif duplicateCheck.unique() == True and column != '#libraryId':
        print(df[duplicateCheck].loc[:,['#libraryId', column]])
    elif duplicateCheck.unique() == True and column == '#libraryId':
        print(df[duplicateCheck].loc[:,['#libraryId']])

# prints all unique values in a specific column
def unique_sorted(df, column):
    unique = df[column].unique()
    unique.sort()
    print(unique)

! python3 $path_to_create_exp_script $experiment_id $path_to_output $experiment_type

/Users/scarsana/Desktop/git/scRNA-Seq/scripts/Create_ExpLib_tables.py:97: SyntaxWarning: invalid escape sequence '\('
  all_protoc = [w.replace('(', '\(') for w in all_protoc]
/Users/scarsana/Desktop/git/scRNA-Seq/scripts/Create_ExpLib_tables.py:98: SyntaxWarning: invalid escape sequence '\)'
  all_protoc = [w.replace(')', '\)') for w in all_protoc] 
Be patient, it may take a few minutes.
0it [00:00, ?it/s]
0 samples dont have attributes, try to find them somewhere else
0it [00:00, ?it/s]
0 samples dont have attributes

lib_matching = pd.read_csv('/Users/scarsana/Desktop/annotate/SRP356459/library_matching_SRP491411_SRP356459.csv', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(lib_matching)

library = pd.read_csv(library_path_from_script, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
# limiting to final columns only b/c display is too big and information from extra columns has already been moved appropriately 
library = library[library_cols]
display_df(library)

infoOrgan = library['infoOrgan'].drop_duplicates().sort_values()
organ_df = pd.DataFrame(infoOrgan)
organ_df = organ_df.reindex(columns=[*organ_df.columns.tolist(), 'notes_anat', 'anatId_', 'anatName_', 'anatAnnotationStatus_', 'infoOrgan_new', 'comment_anat'], fill_value="")
organ_df.to_csv(info_anat_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
if not os.path.exists(info_anat_complete_path): 
    organ_df.to_csv(info_anat_complete_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

# options for anatAnnotationStatus: perfect match, missing child term, other

organ_df_complete = pd.read_csv(info_anat_complete_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(organ_df_complete)

library = library.merge(organ_df_complete, left_on='infoOrgan', right_on='infoOrgan')

library['anatId'] = library['anatId_'].values
library['anatName'] = library['anatName_'].values
library['anatAnnotationStatus'] = library['anatAnnotationStatus_'].values

## optional - update infoOrgan, add anat-specific comments 
#library['infoOrgan'] = library['infoOrgan_new'].values
#library['comment'] = library[['comment', 'comment_anat']].agg(' '.join, axis=1)

# reformat, save progress
library = library[library_cols]
display_df(library)
library.to_csv(library_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

infoStage = library['infoStage'].drop_duplicates().sort_values()
stage_df = pd.DataFrame(infoStage)
stage_df = stage_df.reindex(columns=[*stage_df.columns.tolist(), 'notes_stage', 'stageId_', 'stageName_', 'stageAnnotationStatus_', 'infoStage_new','comment_stage'], fill_value="")
stage_df.to_csv(info_stage_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
if not os.path.exists(info_stage_complete_path): 
    stage_df.to_csv(info_stage_complete_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

# options for stageAnnotationStatus: perfect match, missing child term, other

stage_df_complete = pd.read_csv(info_stage_complete_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(stage_df_complete)

library = library.merge(stage_df_complete, left_on='infoStage', right_on='infoStage')

library['stageId'] = library['stageId_'].values
library['stageName'] = library['stageName_'].values
library['stageAnnotationStatus'] = library['stageAnnotationStatus_'].values

## optional - update infoOrgan, add anat-specific comments 
#library['infoStage'] = library['infoStage_new'].values
#library['comment'] = library[['comment', 'comment_stage']].agg(' '.join, axis=1)

# reformat, save progress
library = library[library_cols]
display_df(library)
library.to_csv(library_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

#library.loc[library["sex"] == "male", "sex"] = "M"
#library.loc[library["sex"] == "female", "sex"] = "F"

#library.loc[:,'strain'] = ''

#library.loc[:,'genotype'] = ''

#library.loc[:,'speciesId'] = ''

# view
display_df(library)

# making these variables because we use them again in the experiment file
# usually 10X Genomics V1/V2/V3/V3.1, Smart-seq, Smart-seq2
my_protocol = '10X Genomics V2'
# Full-length or 3'end or 5'end
my_protocolType = "3'end"

library.loc[:,'protocol'] = my_protocol
library.loc[:,'protocolType'] = my_protocolType
# scRNA-seq, Sn-scRNA-seq
library.loc[:,'RNAseqTags'] = 'scRNA-seq'

# view
display_df(library)

# ex. control, diet, light, reproductive capacity, time post mortem, time post feeding, 
# exercise details, menstruation, personality, litter size 
#library.loc[library["condition"] == "old", "condition"] = "new"

# view
display_df(library)

library.loc[:,'annotatorId'] = 'SAC'
library.loc[:,'lastModificationDate'] = '2024-09-30'

# view
display_df(library)

#library.loc[:,'comment'] = ''

library_file_complete = library[library_cols]

library_file_complete.to_csv(library_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

# view
display_df(library_file_complete)

barcode_column = "barcode"
library_column = "library_name"
cell_type_column = "clusters"

! python3 $path_to_barcodes_script $path_to_output --scRNASeqLibrary $library_to_add_path --barcode_file $path_to_barcode_file --barcode_col $barcode_column --libName_col $library_column --cellType_col $cell_type_column --ignore_check --no_additional_file

There are 11 unique libraries in scRNASeqLibrary.tsv table
There are 11 unique libraries in the barcode table provided
Be extra careful if not same number of libraries in both tables, always manually check the matching names in 'matching_lib_names.tsv' table output
100%|█████████████████████████████████████████| 11/11 [00:00<00:00, 3478.91it/s]
                                    name_Library                               new_lib_name
44836  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
38701  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
42310  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
29717   TL_20-02-2020_greymatter_unsorted_3pr_v3   TL_20-02-2020_greymatter_unsorted_3pr_v3
3342      TL_20-02-2020_greymatter_sorted_3pr_v3     TL_20-02-2020_greymatter_sorted_3pr_v3
33771   TL_20-02-2020_greymatter_unsorted_3pr_v3   TL_20-02-2020_greymatter_unsorted_3pr_v3
41290  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
37696  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
44031  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
61291  TL_24-02-2020_whitematter_unsorted_3pr_v3  TL_24-02-2020_whitematter_unsorted_3pr_v3
57593  TL_24-02-2020_whitematter_unsorted_3pr_v3  TL_24-02-2020_whitematter_unsorted_3pr_v3
53727   TL_24-02-2020_greymatter_unsorted_3pr_v3   TL_24-02-2020_greymatter_unsorted_3pr_v3
38640  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
53056   TL_24-02-2020_greymatter_unsorted_3pr_v3   TL_24-02-2020_greymatter_unsorted_3pr_v3
48666   TL_24-02-2020_greymatter_unsorted_3pr_v3   TL_24-02-2020_greymatter_unsorted_3pr_v3
37626  TL_20-02-2020_whitematter_unsorted_3pr_v3  TL_20-02-2020_whitematter_unsorted_3pr_v3
54377   TL_24-02-2020_greymatter_unsorted_3pr_v3   TL_24-02-2020_greymatter_unsorted_3pr_v3
53537   TL_24-02-2020_greymatter_unsorted_3pr_v3   TL_24-02-2020_greymatter_unsorted_3pr_v3
29505   TL_20-02-2020_greymatter_unsorted_3pr_v3   TL_20-02-2020_greymatter_unsorted_3pr_v3
6076      TL_20-02-2020_greymatter_sorted_3pr_v3     TL_20-02-2020_greymatter_sorted_3pr_v3
0 libraries dont have any barcodes !!
the following libraries don't have any barcodes: set()

lib_names = pd.read_csv(lib_names_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(lib_names)

barcode_file = pd.read_csv(barcode_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

cell_type = barcode_file['cell_type'].drop_duplicates().sort_values()
cell_df = pd.DataFrame(cell_type)
cell_df = cell_df.reindex(columns=[*cell_df.columns.tolist(), 'notes_cell', 'cellTypeId_', 'cellTypeName_', 'cellTypeAnnotationStatus_', 'cell_type_new','comment_cell'], fill_value="")
cell_df.to_csv(info_celltype_path, sep="\t", index=False)
if not os.path.exists(info_celltype_complete_path): 
    cell_df.to_csv(info_celltype_complete_path, sep="\t", index=False)

# options for cellTypeAnnotationStatus: perfect match, missing child term, other

cell_df_complete = pd.read_csv(info_celltype_complete_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(cell_df_complete)

barcode_file = barcode_file.merge(cell_df_complete, left_on='cell_type', right_on='cell_type')

barcode_file['cellTypeId'] = barcode_file['cellTypeId_'].values
barcode_file['cellTypeName'] = barcode_file['cellTypeName_'].values
barcode_file['cellTypeAnnotationStatus'] = barcode_file['cellTypeAnnotationStatus_'].values

# optional - update cell type name and add comments
barcode_file['cell_type'] = barcode_file['cell_type_new'].values
#barcode_file['comment'] = barcode_file[['comment', 'comment_cell']].agg(' '.join, axis=1)

barcode_file_complete = barcode_file[barcode_cols]
display_df(barcode_file_complete)
barcode_file_complete.to_csv(barcode_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

experiment = pd.read_csv(experiment_path_from_script, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
experiment.head()

library_to_add = pd.read_csv(library_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

# this will give you the number of rows in the complete library file 
# this should be the number of annotated libraries
ann_lib = len(library_to_add.index)
len(library_to_add.index)

11

# partial or total
experiment.loc[:,'experimentStatus'] = 'partial'
# scRNA-seq, Sn-scRNA-seq for both we put: 'Sn-scRNA-seq, scRNA-seq'
experiment.loc[:,'RNAseqTags'] = 'scRNA-seq' 


# see above cell, also can add as free text
experiment.loc[:,'numberOfAnnotatedLibraries'] = ann_lib

# these variables should already exist from above but if not can just add as free text
experiment.loc[:,'protocol'] = my_protocol
experiment.loc[:,'protocolType'] = my_protocolType

experiment.head()

experiment.loc[:,'GSE'] = 'GSE256491'
#experiment.loc[:,'Bioproject'] = '' 
#experiment.loc[:,'PMID'] = ''
experiment.loc[:,'reference_url'] = 'https://www.nature.com/articles/s41586-024-07493-y'
#experiment.loc[:,'DOI'] = ''
#experiment.loc[:,'xrefs'] = ''

experiment.head()

experiment.loc[:,'comment'] = 'GEO says 10X Genomics V2, supplemental methods says 10X Genomics V3. it is definitely 10X, i went with V2 but if there are issues when the pipeline is run try changing to V3. also, partially annotated because i only included healthy/control samples'


experiment.head()

experiment.to_csv(experiment_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

library_to_add = pd.read_csv(library_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
experiment_to_add = pd.read_csv(experiment_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

# pull from git and pull in library/experiment file
! git pull
git_library = pd.read_csv(git_library_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
git_experiment = pd.read_csv(git_experiment_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

# library file
if set(library_to_add.columns) == set(git_library.columns):
    print('The columns in the library file match')
else:
    print('The columns in the library file DO NOT MATCH')

# experiment file
if set(experiment_to_add.columns) == set(git_experiment.columns):
    print('The columns in the experiment file match')
else:
    print('The columns in the experiment file DO NOT MATCH')


# maybe to make this something more like "COLUMNS GOOD - LIBRARY" and "COLUMNS BAD - EXPERIMENT"

Already up to date.
The columns in the library file match
The columns in the experiment file match

library_git_plus_new = pd.concat([git_library, library_to_add], ignore_index = True, sort = False)
library_git_plus_new.tail(n=14)

experiment_git_plus_new = pd.concat([git_experiment, experiment_to_add], ignore_index = True, sort = False)
experiment_git_plus_new.tail(n=5)

barcode_file_for_git = pd.read_csv(barcode_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
barcode_file_for_git.head(20)

! git pull

Already up to date.

library_git_plus_new.to_csv(git_library_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
update_format(git_library_path)
experiment_git_plus_new.to_csv(git_experiment_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
update_format(git_experiment_path)
barcode_file_for_git.to_csv(git_barcode_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
update_format(git_barcode_path)

! git status

On branch develop
Your branch is up to date with 'origin/develop'.

Changes not staged for commit:
  (use "git add <file>..." to update what will be committed)
  (use "git restore <file>..." to discard changes in working directory)
	modified:   ../1_sara_scRNA_template.ipynb
	modified:   ../../../scRNA_Seq/scRNASeqExperiment.tsv
	modified:   ../../../scRNA_Seq/scRNASeqLibrary_merged.tsv

Untracked files:
  (use "git add <file>..." to include in what will be committed)
	../../bulk/1_anne_bulk_template.ipynb
	./
	../../../scRNA_Seq/scRNASeq_barcode_SRP491411.tsv

no changes added to commit (use "git add" and/or "git commit -a")

! git add $git_experiment_path $git_library_path $git_barcode_path

! git status

On branch develop
Your branch is up to date with 'origin/develop'.

Changes to be committed:
  (use "git restore --staged <file>..." to unstage)
	modified:   ../../../scRNA_Seq/scRNASeqExperiment.tsv
	modified:   ../../../scRNA_Seq/scRNASeqLibrary_merged.tsv
	new file:   ../../../scRNA_Seq/scRNASeq_barcode_SRP491411.tsv

Changes not staged for commit:
  (use "git add <file>..." to update what will be committed)
  (use "git restore <file>..." to discard changes in working directory)
	modified:   ../1_sara_scRNA_template.ipynb

Untracked files:
  (use "git add <file>..." to include in what will be committed)
	../../bulk/1_anne_bulk_template.ipynb
	./

! git commit -m $commit_message_exp

[develop 59534bd] adding annotated scRNA experiment SRP491411
 3 files changed, 61874 insertions(+)
 create mode 100644 scRNA_Seq/scRNASeq_barcode_SRP491411.tsv

! git push

Enumerating objects: 10, done.
Counting objects: 100% (10/10), done.
Delta compression using up to 12 threads
Compressing objects: 100% (6/6), done.
Writing objects: 100% (6/6), 396.90 KiB | 1.21 MiB/s, done.
Total 6 (delta 5), reused 0 (delta 0), pack-reused 0
remote: 
remote: To create a merge request for develop, visit:
remote:   https://gitlab.sib.swiss/Bgee/expression-annotations/-/merge_requests/new?merge_request%5Bsource_branch%5D=develop
remote: 
To https://gitlab.sib.swiss/Bgee/expression-annotations.git
   fb6c1fe..59534bd  develop -> develop

! git status

! git add $path_to_output

! git commit -m $commit_message_py

! git push

	cell_type	notes_cell	cellTypeId_	cellTypeName_	cellTypeAnnotationStatus_	cell_type_new
0	Angiogenic capillary	Angiogenesis is the growth of blood vessels from the existing vasculature	CL:0002144	capillary endothelial cell	missing child term	Angiogenic capillary endothelial cell
1	Arteriole		CL:1000412	endothelial cell of arteriole	perfect match	Arteriole endothelial cell
2	Artery		CL:1000413	endothelial cell of artery	perfect match	Artery endothelial cell
3	Astrocytes		CL:0000127	astrocyte	perfect match	Astrocytes
4	Capillary		CL:0002144	capillary endothelial cell	perfect match	Capillary endothelial cell
5	EndoMT	Endothelial to mesenchymal transition (EndMT) is a process whereby an endothelial cell undergoes a series of molecular events that lead to a change in phenotype toward a mesenchymal cell - there isn't enough literature for me to request a new term for EndMT	CL:0000000	cell	other	EndoMT: endothelial-to-mesenchymal transitional cells
6	Endothelial cells		CL:0000115	endothelial cell	perfect match	Endothelial cells
7	Fibroblasts		CL:0000057	fibroblast	perfect match	Fibroblasts
8	Large artery		CL:1000413	endothelial cell of artery	missing child term	Large artery endothelial cell
9	Large vein		CL:0002543	vein endothelial cell	missing child term	Large vein endothelial cell
10	Microglia and Macrophages	microglial cell is child of macrophage, annotating as macrophage	CL:0000235	macrophage	other	Microglia and Macrophages
11	Mitochondrial	weird that they kept these, keeping as just cell	CL:0000000	cell	other	Mitochondrial
12	Neuron progenitor		CL:0011020	neural progenitor cell	other	Neuron progenitor
13	Neurons		CL:0000540	neuron	perfect match	Neurons
14	Oligodendrocytes		CL:0000128	oligodendrocyte	perfect match	Oligodendrocytes
15	Pericytes		CL:0000669	pericyte	perfect match	Pericytes
16	Proliferating cell	this cluster comes from the EC specific cluster, so this is a proliferating EC not just a proliferating cell	CL:0000115	endothelial cell	missing child term	Proliferating endothelial cell
17	Smooth muscle cells		CL:0000192	smooth muscle cell	perfect match	Smooth muscle cells
18	Stem cells		CL:0000034	stem cell	perfect match	Stem cells
19	Stem-to-EC	A mesenchymal stem cell capable of developing into blood vessel endothelium - seems the closest term to stem to EC	CL:0000566	angioblastic mesenchymal cell	other	Stem-to-endothelial cell transdifferentiating
20	T-cells		CL:0000084	T cell	perfect match	T-cells
21	Vein		CL:0002543	vein endothelial cell	perfect match	Vein endothelial cell
22	Venule		CL:1000414	endothelial cell of venule	perfect match	Venule endothelial cell

	infoOrgan	notes_anat	anatId_	anatName_	anatAnnotationStatus_
0	brain - CNS	they describe as brain and other times CNS, going with brain because i think here they are using CNS as general, not to suggest they are including the spinal cord	UBERON:0000955	brain	perfect match
1	right temporal lobe		UBERON:0002809	right temporal lobe	perfect match
2	right temporal lobe - grey matter	synonym of temporal cortex is gray matter of temporal lobe	UBERON:0016538	temporal cortex	missing child term
3	right temporal lobe - white matter		UBERON:0016534	white matter of temporal lobe	missing child term

	infoStage	notes_stage	stageId_	stageName_	stageAnnotationStatus_
0	12.4 gestational weeks	12.4 gestational weeks - 10.4 wpf, 72.8 dpf	HsapDv:0000048	11th week post-fertilization stage	missing child term
1	24 years		HsapDv:0000118	24-year-old stage	perfect match
2	25 years		HsapDv:0000119	25-year-old stage	perfect match
3	39 years		HsapDv:0000133	39-year-old stage	perfect match
4	9.1 gestational weeks	9.1 gestational weeks - 7.1 wpf, 49.7 dpf	HsapDv:0000026	Carnegie stage 19	missing child term

	experimentId	#libraryId	FINAL_barcode	lib_name_SRA	lib_GEO
0	SRP491411	SRX23721836	12point4_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1	FETAL_brain_6_all cells	FETAL_brain_6_all cells
1	SRP491411	SRX23721835	TL_24-02-2020_whitematter_unsorted_3pr_v3	TL_patient10_all cells_2	TL_patient10_all cells_2
2	SRP491411	SRX23721834	TL_24-02-2020_greymatter_unsorted_3pr_v3	TL_patient10_all cells_1	TL_patient10_all cells_1
3	SRP491411	SRX23721833	TL_24-02-2020_whitematter_sorted_3pr_v3	TL_patient10_EC_2	TL_patient10_EC_2
4	SRP491411	SRX23721832	TL_24-02-2020_greymatter_sorted_2ndbatch_3pr_v3	TL_patient10_EC_1	TL_patient10_EC_1
5	SRP491411	SRX23721831	9point1_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1	FETAL_brain_8_all cells	FETAL_brain_8_all cells
6	SRP491411	SRX23721826	TL7	TL_patient7_EC	TL_patient7_EC
7	SRP491411	SRX23721825	TL_20-02-2020_whitematter_unsorted_3pr_v3	TL_patient9_all cells_2	TL_patient9_all cells_2
8	SRP491411	SRX23721824	TL_20-02-2020_greymatter_unsorted_3pr_v3	TL_patient9_all cells_1	TL_patient9_all cells_1
9	SRP491411	SRX23721823	TL_20-02-2020_whitematter_sorted_3pr_v3	TL_patient9_EC_2	TL_patient9_EC_2
10	SRP491411	SRX23721822	TL_20-02-2020_greymatter_sorted_3pr_v3	TL_patient9_EC_1	TL_patient9_EC_1
11	SRP356459	SRX13883104	15point5_Weeks_Fetal_Heart_Sorted_3pr_v3_1	15point5_Weeks_Fetal_Heart_Sorted_3pr_v3_1	FETAL_periphery_IND5.1_EC
12	SRP356459	SRX13883088	12point4_Weeks_Fetal_Arm_SORTED_3pr_v3_1	12point4_Weeks_Fetal_Arm_SORTED_3pr_v3_1	FETAL_periphery_IND6_EC
13	SRP356459	SRX13883081	15point5_Weeks_Fetal_Arm_Sorted_3pr_v3_1	15point5_Weeks_Fetal_Arm_Sorted_3pr_v3_1	FETAL_periphery_IND5_EC
14	SRP356459	SRX13883071	14-4_16-4_weeks_Fetal_CNS_Sorted_pooled_3pr_v3	14-4_16-4_weeks_Fetal_CNS_Sorted_pooled_3pr_v3	FETAL_brain_IND2_IND3_EC
15	SRP356459	SRX13883070	Fetal_CNS_20-10-2020_sorted_3pr_v3	Fetal_CNS_20-10-2020_sorted_3pr_v3	FETAL_brain_IND1_EC
16	SRP356459	SRX13883067	18wk_Fetal_Leg_Sorted_3pr_v3_1	18wk_Fetal_Leg_Sorted_3pr_v3_1	FETAL_periphery_IND4_EC
17	SRP356459	SRX13883064	TL_27-01-2020_EC_3pr_v3	TL_27-01-2020_EC	TL_patient6_EC
18	SRP356459	SRX13883063	TL_10-10-2019_ECs	TL_10-10-2019_ECs	TL_patient5_EC
19	SRP356459	SRX13883062	TLE	TLE_19_03_2019	TL_patient4_EC
20	SRP356459	SRX13883061	temporal_lobe_20190219	temporal_lobe_20190219	TL_patient3_EC
21	SRP356459	SRX13883058	15point5_Weeks_Fetal_CNS_Sorted_3pr_v3_1	15point5_Weeks_Fetal_CNS_Sorted_3pr_v3_1	FETAL_brain_IND5_EC
22	SRP356459	SRX13883057	18wk_Fetal_CNS_Sorted_3pr_v3_1	18wk_Fetal_CNS_Sorted_3pr_v3_1	FETAL_brain_IND4_EC
23	SRP356459	SRX13883048	15point5_Weeks_Fetal_Throat_Sorted_3pr_v3_1	15point5_Weeks_Fetal_Throat_Sorted_3pr_v3_1	FETAL_periphery_IND5.3_EC
24	SRP356459	SRX13883045	TLE_White-matter_Unsorted_3pr_v3	TLE_White-matter_Unsorted_3pr_v3	TL_patient10_all cells
25	SRP356459	SRX13883044	TLE_Grey-matter_Unsorted_3pr_v3	TLE_Grey-matter_Unsorted_3pr_v3	TL_patient9_all cells
26	SRP356459	SRX13883043	TLE_Grey-White-Interface_Unsorted_3pr_v3	TLE_Grey-White-Interface_Unsorted_3pr_v3	TL_patient8_all cells
27	SRP356459	SRX13883042	Combined_White_GreyPia_WhiteGreyPia_03-11-2020_Unsorted_3pr_v3	Combined_White_GreyPia_WhiteGreyPia_03-11-2020_Unsorted_3pr_v3	TL_patient7_all cells
28	SRP356459	SRX13883041	TL_27-01-2020_unsorted_3pr_v3	TL_27-01-2020_unsorted_3pr_v3	TL_patient6_all cells
29	SRP356459	SRX13883040	TL_10-10-2019_unsorted	TL_10-10-2019_unsorted	TL_patient5_all cells
30	SRP356459	SRX13883039	15point5_Weeks_Fetal_CNS_Unsorted_3pr_v3_1	15point5_Weeks_Fetal_CNS_Unsorted_3pr_v3_1	FETAL_brain_5_all cells
31	SRP356459	SRX13883038	18wk_Fetal_CNS_Unsorted_3pr_v3_1	18wk_Fetal_CNS_Unsorted_3pr_v3_1	FETAL_brain_4_all cells
32	SRP356459	SRX13883037	15point5_Weeks_Fetal_Kidney_Sorted_3pr_v3_1	15point5_Weeks_Fetal_Kidney_Sorted_3pr_v3_1	FETAL_periphery_IND5.2_EC
33	SRP356459	SRX13883036	16-4weeks_Fetal_CNS_Unsorted_3pr_v3	16-4weeks_Fetal_CNS_Unsorted_3pr_v3	FETAL_brain_3_all cells
34	SRP356459	SRX13883035	14-4weeks_Fetal_CNS_Unsorted_3pr_v3	14-4weeks_Fetal_CNS_Unsorted_3pr_v3	FETAL_brain_2_all cells
35	SRP356459	SRX13883034	Fetal_CNS_20-10-2020_unsorted_3pr_v3	Fetal_CNS_20-10-2020_unsorted_3pr_v3	FETAL_brain_1_all cells
36	SRP356459	SRX13883032	16-4weeks_Fetal_HeartandLung_Sorted_3pr_v3	16-4weeks_Fetal_HeartandLung_Sorted_3pr_v3	FETAL_periphery_IND3_EC
37	SRP356459	SRX13883031	4weeks_Fetal_Muscle_Sorted_3pr_v3	14-4weeks_Fetal_Muscle_Sorted_3pr_v3	FETAL_periphery_IND2_EC

	#libraryId	experimentId	platform	SRSId	url_GSM	infoOrgan	infoCellType_abInitio	infoStage	sex	speciesId	protocol	protocolType	lib_name	sampleName	lastModificationDate
0	SRX23721836	SRP491411	Illumina NovaSeq 6000	SRS20549925	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101607	brain - CNS	Endothelial, perivascular and other tissue derived cells	12.4 gestational weeks	NA	9606	10X Genomics V2,10X Genomics	3'end	12point4_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1	SAMN40082466	30/09/2024
1	SRX23721835	SRP491411	Illumina NovaSeq 6000	SRS20551511	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101601	right temporal lobe - white matter	Endothelial, perivascular and other tissue derived cells	24 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_24-02-2020_whitematter_unsorted_3pr_v3	SAMN40082472	30/09/2024
2	SRX23721834	SRP491411	Illumina NovaSeq 6000	SRS20552142	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101600	right temporal lobe - grey matter	Endothelial, perivascular and other tissue derived cells	24 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_24-02-2020_greymatter_unsorted_3pr_v3	SAMN40082473	30/09/2024
3	SRX23721833	SRP491411	Illumina NovaSeq 6000	SRS20552356	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101599	right temporal lobe - white matter	Endothelial cells	24 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_24-02-2020_whitematter_sorted_3pr_v3	SAMN40082474	30/09/2024
4	SRX23721832	SRP491411	Illumina NovaSeq 6000	SRS20549927	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101598	right temporal lobe - grey matter	Endothelial cells	24 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_24-02-2020_greymatter_sorted_2ndbatch_3pr_v3	SAMN40082475	30/09/2024
5	SRX23721831	SRP491411	Illumina NovaSeq 6000	SRS20551510	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101606	brain - CNS	Endothelial, perivascular and other tissue derived cells	9.1 gestational weeks	NA	9606	10X Genomics V2,10X Genomics	3'end	9point1_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1	SAMN40082467	30/09/2024
6	SRX23721826	SRP491411	Illumina NovaSeq 6000	SRS20552352	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101597	right temporal lobe	Endothelial cells	39 years	F	9606	10X Genomics V2,10X Genomics	3'end	TL7	SAMN40082476	30/09/2024
7	SRX23721825	SRP491411	Illumina NovaSeq 6000	SRS20551508	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101596	right temporal lobe - white matter	Endothelial, perivascular and other tissue derived cells	25 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_20-02-2020_whitematter_unsorted_3pr_v3	SAMN40082477	30/09/2024
8	SRX23721824	SRP491411	Illumina NovaSeq 6000	SRS20552354	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101595	right temporal lobe - grey matter	Endothelial, perivascular and other tissue derived cells	25 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_20-02-2020_greymatter_unsorted_3pr_v3	SAMN40082478	30/09/2024
9	SRX23721823	SRP491411	Illumina NovaSeq 6000	SRS20552353	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101594	right temporal lobe - white matter	Endothelial cells	25 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_20-02-2020_whitematter_sorted_3pr_v3	SAMN40082479	30/09/2024
10	SRX23721822	SRP491411	Illumina NovaSeq 6000	SRS20552141	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM8101593	right temporal lobe - grey matter	Endothelial cells	25 years	M	9606	10X Genomics V2,10X Genomics	3'end	TL_20-02-2020_greymatter_sorted_3pr_v3	SAMN40082480	30/09/2024

SRP491411 / GSE256491 and SRP356459 / GSE256490¶

annotation summary¶

10X - barcodes and annotations¶

script¶

library file prep¶

manual updates to library files¶

library annnotations¶

anatomical entity¶

stage¶

sex, strain, genotype, speciesId¶

protocol & RNAseqTags¶

condition¶

annotator id, last modification date¶

comments¶

save complete file with correct columns¶

script - barcode (10X only)¶

check library names match¶

cell type annotation - 10X version¶

experiment annotations¶

experiment and protocol details¶

paper and xrefs¶

comments¶

save complete file¶

QA time¶

to add things here¶

check columns match¶

view files¶

add annotations to git¶

add annotation folder and script to git¶

	from_barcode_table	from_lib_table
0	12point4_Weeks_Fetal_CNS__3pr_v3_1	12point4_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1
1	9point1_Weeks_Fetal_CNS__3pr_v3_1	9point1_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1
2	TL7	TL7
3	TL_20-02-2020_greymatter_sorted_3pr_v3	TL_20-02-2020_greymatter_sorted_3pr_v3
4	TL_20-02-2020_greymatter_unsorted_3pr_v3	TL_20-02-2020_greymatter_unsorted_3pr_v3
5	TL_20-02-2020_whitematter_sorted_3pr_v3	TL_20-02-2020_whitematter_sorted_3pr_v3
6	TL_20-02-2020_whitematter_unsorted_3pr_v3	TL_20-02-2020_whitematter_unsorted_3pr_v3
7	TL_24-02-2020_greymatter_sorted_2ndbatch_3pr_v3	TL_24-02-2020_greymatter_sorted_2ndbatch_3pr_v3
8	TL_24-02-2020_greymatter_unsorted_3pr_v3	TL_24-02-2020_greymatter_unsorted_3pr_v3
9	TL_24-02-2020_whitematter_sorted_3pr_v3	TL_24-02-2020_whitematter_sorted_3pr_v3
10	TL_24-02-2020_whitematter_unsorted_3pr_v3	TL_24-02-2020_whitematter_unsorted_3pr_v3

	#libraryId	experimentId	platform	SRSId	anatId	anatName	stageId	stageName	url_GSM	infoOrgan	infoCellType_abInitio	infoStage	anatAnnotationStatus	stageAnnotationStatus	sex	speciesId	RNAseqTags	protocol	protocolType	lib_name	sampleName	comment	annotatorId	lastModificationDate
58217	SRX13883034	SRP356459	Illumina NovaSeq 6000	SRS11751845	UBERON:0000955	brain	HsapDv:0000026	Carnegie stage 19		brain - CNS	Perivascular and other tissue derived cells	9 gestational weeks	perfect match	missing child term	NA	9606	scRNA-seq	10X Genomics V2	3'end	Fetal_CNS_20-10-2020_unsorted_3pr_v3	SAMN25224383	control/healthy samples only, removed all dise...	SAC	2024-09-26
58218	SRX13883032	SRP356459	Illumina NovaSeq 6000	SRS11751842	UBERON:0000062	organ	HsapDv:0000052	15th week post-fertilization stage		peripheral organs - heart and lung	Endothelial cells	16.4 gestational weeks	other	missing child term	NA	9606	scRNA-seq	10X Genomics V2	3'end	16-4weeks_Fetal_HeartandLung_Sorted_3pr_v3	SAMN25224337	control/healthy samples only, removed all dise...	SAC	2024-09-26
58219	SRX13883031	SRP356459	Illumina NovaSeq 6000	SRS11751843	UBERON:0002113	kidney	HsapDv:0000050	13th week post-fertilization stage		peripheral organs - kidney	Endothelial cells	14.4 gestational weeks	perfect match	missing child term	NA	9606	scRNA-seq	10X Genomics V2	3'end	4weeks_Fetal_Muscle_Sorted_3pr_v3	SAMN25224336	control/healthy samples only, removed all dise...	SAC	2024-09-26
58220	SRX23721836	SRP491411	Illumina NovaSeq 6000	SRS20549925	UBERON:0000955	brain	HsapDv:0000048	11th week post-fertilization stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	brain - CNS	Endothelial, perivascular and other tissue der...	12.4 gestational weeks	perfect match	missing child term	NA	9606	scRNA-seq	10X Genomics V2	3'end	12point4_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1	SAMN40082466		SAC	2024-09-30
58221	SRX23721835	SRP491411	Illumina NovaSeq 6000	SRS20551511	UBERON:0016534	white matter of temporal lobe	HsapDv:0000118	24-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - white matter	Endothelial, perivascular and other tissue der...	24 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_24-02-2020_whitematter_unsorted_3pr_v3	SAMN40082472		SAC	2024-09-30
58222	SRX23721834	SRP491411	Illumina NovaSeq 6000	SRS20552142	UBERON:0016538	temporal cortex	HsapDv:0000118	24-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - grey matter	Endothelial, perivascular and other tissue der...	24 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_24-02-2020_greymatter_unsorted_3pr_v3	SAMN40082473		SAC	2024-09-30
58223	SRX23721833	SRP491411	Illumina NovaSeq 6000	SRS20552356	UBERON:0016534	white matter of temporal lobe	HsapDv:0000118	24-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - white matter	Endothelial cells	24 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_24-02-2020_whitematter_sorted_3pr_v3	SAMN40082474		SAC	2024-09-30
58224	SRX23721832	SRP491411	Illumina NovaSeq 6000	SRS20549927	UBERON:0016538	temporal cortex	HsapDv:0000118	24-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - grey matter	Endothelial cells	24 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_24-02-2020_greymatter_sorted_2ndbatch_3pr_v3	SAMN40082475		SAC	2024-09-30
58225	SRX23721831	SRP491411	Illumina NovaSeq 6000	SRS20551510	UBERON:0000955	brain	HsapDv:0000026	Carnegie stage 19	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	brain - CNS	Endothelial, perivascular and other tissue der...	9.1 gestational weeks	perfect match	missing child term	NA	9606	scRNA-seq	10X Genomics V2	3'end	9point1_Weeks_Fetal_CNS_UNSORTED_3pr_v3_1	SAMN40082467		SAC	2024-09-30
58226	SRX23721826	SRP491411	Illumina NovaSeq 6000	SRS20552352	UBERON:0002809	right temporal lobe	HsapDv:0000133	39-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe	Endothelial cells	39 years	perfect match	perfect match	F	9606	scRNA-seq	10X Genomics V2	3'end	TL7	SAMN40082476		SAC	2024-09-30
58227	SRX23721825	SRP491411	Illumina NovaSeq 6000	SRS20551508	UBERON:0016534	white matter of temporal lobe	HsapDv:0000119	25-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - white matter	Endothelial, perivascular and other tissue der...	25 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_20-02-2020_whitematter_unsorted_3pr_v3	SAMN40082477		SAC	2024-09-30
58228	SRX23721824	SRP491411	Illumina NovaSeq 6000	SRS20552354	UBERON:0016538	temporal cortex	HsapDv:0000119	25-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - grey matter	Endothelial, perivascular and other tissue der...	25 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_20-02-2020_greymatter_unsorted_3pr_v3	SAMN40082478		SAC	2024-09-30
58229	SRX23721823	SRP491411	Illumina NovaSeq 6000	SRS20552353	UBERON:0016534	white matter of temporal lobe	HsapDv:0000119	25-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - white matter	Endothelial cells	25 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_20-02-2020_whitematter_sorted_3pr_v3	SAMN40082479		SAC	2024-09-30
58230	SRX23721822	SRP491411	Illumina NovaSeq 6000	SRS20552141	UBERON:0016538	temporal cortex	HsapDv:0000119	25-year-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	right temporal lobe - grey matter	Endothelial cells	25 years	missing child term	perfect match	M	9606	scRNA-seq	10X Genomics V2	3'end	TL_20-02-2020_greymatter_sorted_3pr_v3	SAMN40082480		SAC	2024-09-30

	#experimentId	experimentName	experimentDescription	experimentSource	experimentStatus	RNAseqTags	numberOfAnnotatedLibraries	protocol	protocolType	GSE	Bioproject	PMID	reference_url	DOI	xrefs	comment
98	SRP462115	Unravelling cell type specific response to Par...	Parkinson’s Disease (PD) is the second most co...	SRA	partial	Sn-scRNA-seq	14 libraries, but barcode file contains info f...	10X Genomics V3	3'end	GSE243639	PRJNA1019314	38245794	https://molecularneurodegeneration.biomedcentr...	10.1186/s13024-023-00699-0		barcode file is sheet ‘HighLevelCellTypes’ fro...
99	SRP192549	Single-cell transcriptomic profiling of the ag...	The mammalian brain is complex, with multiple ...	SRA	total	scRNA-seq	16 libraries	10X Genomics V2	3'end	GSE129788	PRJNA532831	31551601	https://www.nature.com/articles/s41593-019-0491-3	10.1038/s41593-019-0491-3	https://singlecell.broadinstitute.org/single_c...	annotation of cell types may be improved in th...
100	SRP125125	RNA-Seq profiling of 29 immune cell types and ...	We performed RNA-Seq transcriptome profiling o...	SRA	total	scRNA-seq	127 libraries	Adapted Smart-Seq2	Full-length	GSE107011	PRJNA418779	30726743	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6...	10.1016/j.celrep.2019.01.041	30528453[PMID]	NTR to check for annotation improvement, see h...
101	SRP356459	Molecular atlas of the human brain vasculature...	Molecular atlas of the human brain vasculature...	SRA	partial	scRNA-seq	27	10X Genomics V2	3'end	GSE256490	PRJNA800024	38987604	https://www.nature.com/articles/s41586-024-074...	10.1038/s41586-024-07493-y		GEO says 10X Genomics V2, supplemental methods...
102	SRP491411	Single-cell atlas of the human brain vasculatu...	A broad range of brain pathologies critically ...	SRA	partial	scRNA-seq	11	10X Genomics V2	3'end	GSE256491	PRJNA1079775	38987604	https://www.nature.com/articles/s41586-024-074...	10.1038/s41586-024-07493-y		GEO says 10X Genomics V2, supplemental methods...

	barcode	library	experiment	tissue	cell_type	cellTypeId	cellTypeName	cellTypeAnnotationStatus	name_Library
0	AAACCCAAGGACGGAG	SRX23721822	SRP491411	right temporal lobe - grey matter	Large artery endothelial cell	CL:1000413	endothelial cell of artery	missing child term	TL_20-02-2020_greymatter_sorted_3pr_v3
1	AAACCCAGTCTGTCAA	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
2	AAACCCAGTGATTAGA	SRX23721822	SRP491411	right temporal lobe - grey matter	Artery endothelial cell	CL:1000413	endothelial cell of artery	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
3	AAACCCAGTTGTGGCC	SRX23721822	SRP491411	right temporal lobe - grey matter	Large artery endothelial cell	CL:1000413	endothelial cell of artery	missing child term	TL_20-02-2020_greymatter_sorted_3pr_v3
4	AAACCCATCTGAACGT	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
5	AAACGAAAGAGATTCA	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
6	AAACGAAAGTCACGAG	SRX23721822	SRP491411	right temporal lobe - grey matter	Large artery endothelial cell	CL:1000413	endothelial cell of artery	missing child term	TL_20-02-2020_greymatter_sorted_3pr_v3
7	AAACGAACAGCTCTGG	SRX23721822	SRP491411	right temporal lobe - grey matter	Capillary endothelial cell	CL:0002144	capillary endothelial cell	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
8	AAACGAACAGGAAGTC	SRX23721822	SRP491411	right temporal lobe - grey matter	Large artery endothelial cell	CL:1000413	endothelial cell of artery	missing child term	TL_20-02-2020_greymatter_sorted_3pr_v3
9	AAACGCTAGGCTCCCA	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
10	AAACGCTAGTCATGAA	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
11	AAACGCTAGTCCGTCG	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
12	AAACGCTGTCGAACAG	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
13	AAACGCTTCAAGGCTT	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
14	AAACGCTTCACTTCTA	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
15	AAACGCTTCATACGAC	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
16	AAACGCTTCGGAGCAA	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
17	AAACGCTTCTACTGCC	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
18	AAACGCTTCTCTCGAC	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3
19	AAAGAACAGATGTTAG	SRX23721822	SRP491411	right temporal lobe - grey matter	Arteriole endothelial cell	CL:1000412	endothelial cell of arteriole	perfect match	TL_20-02-2020_greymatter_sorted_3pr_v3